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Table 3 CNN architecture with its layers and parameters

From: High-dimensional aerodynamic data modeling using a machine learning method based on a convolutional neural network

Layer type

CNN-1

CNN-2

CNN-3

CNN-4

Input

109×1

109×1

109×1

109×1

First convolution

16, 3×1, 2×1

16, 3×1, 2×2

16, 3×1, 2×1

16, 3×1, 2×1

Second convolution

-

32, 3×1, 2×2

32, 3×1, 2×1

32, 3×1, 2×1

Third convolution

-

-

64, 3×1, 2×1

64, 3×1, 2×1

Fourth convolution

-

-

-

128, 3×1, 2×1

Fully-connected

3×128

3×128

3×128

3×128

Output

3×1

3×1

3×1

3×1